metadata
language:
- ja
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Small Ja - Vick
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: 'Common Voice 13 - whisper_small on ASR_JA '
type: mozilla-foundation/common_voice_13_0
config: ja
split: test
args: ja
metrics:
- name: Wer
type: wer
value: 622.012752980316
Whisper Small Ja - Vick
This model is a fine-tuned version of openai/whisper-small on the Common Voice 13 - whisper_small on ASR_JA dataset. It achieves the following results on the evaluation set:
- Loss: 0.5735
- Wer Ortho: 731.1720
- Wer: 622.0128
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.1701 | 1.13 | 500 | 0.4424 | 480.6484 | 2104.7685 |
| 0.0606 | 2.26 | 1000 | 0.4455 | 238.1393 | 1241.4749 |
| 0.0334 | 3.39 | 1500 | 0.4821 | 496.1941 | 1038.0787 |
| 0.0167 | 4.52 | 2000 | 0.4851 | 614.7604 | 1104.6160 |
| 0.0113 | 5.66 | 2500 | 0.5100 | 265.9686 | 457.5270 |
| 0.007 | 6.79 | 3000 | 0.5387 | 338.3004 | 569.8087 |
| 0.0072 | 7.92 | 3500 | 0.5301 | 213.4515 | 597.5880 |
| 0.005 | 9.05 | 4000 | 0.5735 | 731.1720 | 622.0128 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1